What is Money?

When you think of money, I bet your US Dollar note or Cambodian Riel note should come to your mind. Well, it is partly true. Your note is one of the form of money called fiat currency. Money is more than just the paper you put in your wallet. Back in the past, people used to use gold or silver as money. Money can come in any type of form as long as it is generally accepted in the exchange of goods and service. This article from the Guardian paints a much better picture that money can just be anything. Prisoners used to accept cigarette as money within the prison economy (have you watched the classic movie called Shawshank Redemption?) then mackerel can and now ramen. So what are the functions of money?

The first essential function of money is that it is a medium of exchange. Money is used to facilitate the exchange of goods and service. Imagine a world without money. It would be a nightmare to buy or sell stuff in the economy. Say you are corn farmer and want to buy 2 kg of meat from a seller but the seller will only sell the meat if you have 5 kg of apple. In order to buy the meat, you will need to find other sellers who are selling apple and is willing to exchange 5 kg of apple with your 5 kg of corn. You would have to chase other sellers if the apple seller only settles for other goods. This kind of system that the exchange of goods is made with other kinds of goods is called "barter system". Therefore, money which is accepted by all parties will reduce the inefficiency of having to chase apple and other produce to buy 2 kg of meat. Meanwhile, prisoners can also exchange all sort of goods and service in the jail which makes life a lot easier.

Money also function as a unit of account. In a plain word, it means that money indicates to others the measure of value of goods and service. Money makes it easy to under its value. For instance, 1 kg of meat cost 10$, 1 kg of corn cost 1$ and 1 kg of apple cost 5$. Therefore, we can know for sure the value of meat, corn and apple. Wouldn't it be more complicate if we only know that 1 kg of meat equals to 10 kg of corn and 1 kg of apple equals to 5 kg of corn. How about the relative value between meat and corn or beef, veggie and so on? It is a lot easier to have a common unit in terms of money for those produce.

Another important function of money is that it has to store value. If we hold 100$ note today, we are almost certain that 30 days later the value of the dollar note is still 100$ and people will accept our 100$ note (let's get inflation out of the equation for simple explanation). The fiat money works well as money in the economy because it is light, durable (unlike gold or silver which is super heavy) and will hold its value in the future. This reasons also explain why prisoners choose cigarette and now ramen as a form of money. Ramen can last a very long time. It is not very heavy to carry around or store it. Other stuff might not be a great form of money. For example, milk is a terrible choice for money. It can get spoiled easily. One needs to always store it in a fridge. The value of milk today should worth nothing in a month time because the milk is spoiled and no one is going to accept it in the exchange of goods and service.

One thing to take away from this article is that when you think of money, it can be more than just a piece of paper. Well, it can be the noodle that you eat when you run out of cash at the end of the month.

Is the Goal of Higher Education to make its Graduates and the Country Rich?

I recently had a conversation with my friend who is a software developer. He said his current job would only need a person with 6 months of rigorous computer programming training. The current programming language that he is using was not even taught during his 4-year college education. Come to think of it and being inspired by a book written by Ha-Joon Chang, a South Korean economist, is the goal of tertiary/higher education to make its graduates rich and thus the country rich?

College education is in high demand at the moment both in the developed and developing countries. In a country like Cambodia where almost 70% of the population is under the age of 35, the number of young people going to college is increasing dramatically. One of the major reason that fuels the demand for college education is the parent’s and young people’s hope of high salary (for most people) and employers demanding college graduates for a vacant position. Basically, there is a trend for employers to search for candidates with a college degree, which significantly increases the demand for college education among young people. Those who do not have a college degree are facing the risk of being put at a disadvantage. It is understandable why employers place a lot of emphasis on college degree. The reason is employers are looking for employees who are competent, knowledgeable, hardworking and reliable. One of the best proxies (a representation of something) to determine such qualities is a college degree. A college-educated person is more likely to be a smart, competent and hardworking person. One, colleges teach a number of subjects that should help graduates to function in their new roles. Two, one must have put a significant amount of effort to endure the gruesome 4 years in college. Third, college graduates should be accustomed (to a certain extent) to an environment which demands great teamwork and leadership, as can be learned during group assignment, clubs or other leadership roles within the school.

While 4 years of college education teaches you a lot, I think it is safe to say one does not use everything that they learn at school and applies them in the daily tasks of one's work. My friend who is a software development does not use Photoshop, Statistics, History or Geography for his daily work. He learned a new programming language through on-the-job training. My point is that a bachelor degree is definitely important, but the society should not put too much hope on bachelor degree alone to solve the society’s problems and to make the country rich. For a few positions like a cook, a technician, a website designer or programmer, a 1 or 2 year vocational training should be enough to perform the roles required for this position. An employer should not disqualify the applicants who is not a college graduate.

It is important to understand that, as put by Ha-Joon Chang, not everything that is taught at the formal education is meant to make the students richer or to promote the prosperity of a nation. A typical businessman or an investment banker does not use chemistry, biology, history or geography lesson that is taught in high school or sociology, environmental studies, philosophy and music taught in the foundation year of college. These subjects are taught to help people to live a more meaningful life and to become a good citizen within the society.

The downside of putting too much emphasis on tertiary education is that it puts the country at a dangerous trajectory where not having a college degree means you are not smart enough and you are not favorable to your potential employers. One of my Chinese friends said many Chinese want to get a Master or even PhD degree to stand a better chance of being recruited, since the job competition in China is very fierce. The time and money that one spends is an opportunity cost. Not everyone can afford higher education and a number of jobs does not require 11 years of higher education. From a pure economic point of view, the resource (time and money) should be spent elsewhere that generates a better return on investment. Some subjects taught at the university are not relevant to one’s workplace. Many important skills and qualities can be learned through on-the-job training including technical knowledge, leadership, teamwork, and self-discipline.

I am not trying to claim that there is no value in higher education. I, myself, have benefited a lot from higher education. I have a broader perspective of the world and live an independent life thanks to higher education. But the society should not believe that only college graduates are competent and rule out applicants without a college degree. In addition, to better prepares college students for their professional work, companies and universities should closely collaborate to design a curriculum that. We should conclude this article to remember that the goal of education is not to make a country financially rich. The reason to invest in education is to help citizen think critically, live a meaningful life and become a good citizen within the society. 

Economics and Woman Empowerment

One says if you teach a parrot to repeat the words - supply and demand- there you go, you can produce an economist. I find it very witty and funny but economics is more than that. One funny analogy is to say that pop music is all about Justin Bieber. Ok here's a better analogy. To say economics is about supply demand is equivalent to say Cambodia is all about Angkor Wat and temples. Yes, Angkor Wat is an indispensable wonder which puts Cambodia on the world map, but Cambodia has more things to offer besides the beautiful Angkor Wat. Similarly, we can use the basic concept of supply and demand as a framework for our analysis on many social phenomenon. 

The mind-boggling thing about economics is that you can see economics everywhere you go. (Credit to our friend at Economind for the inspiration.) Should you use your last $10 on drinking with your friends or $10 phone card to call your bae? That is an economic question related with cost and benefit and which alternatives produce the higher level of satisfaction and happiness or what economists like to call “utility”. (The term utility is a bit vague and I’m pretty confident that it is very very similar to satisfaction and happiness. I hope our friend at Economind would share the same understanding) Should you send a girl to school or force her to help family at home? Yes, it’s more about gender equality and education but I can assure you that it has everything to do with economics. You see, an educated woman can participate in the labor force and labor is a scarce resource to the economy. We don’t have an infinite amount labor to produce goods and service, so we have to be clever in allocating the labor in a way that produce the most output “as many and fast as possible”. Economists also have a term for that. It’s called “efficiency”. Making a woman stay at home may not be the most efficient way to utilize her labor. She may be able to be involved in other activities that generate more social or personal benefit, be it a manager, a teacher, a salesperson, a factory worker and so on. An educated woman produces more than just income for household. A study found that a child born to an educated mother is “50%” more likely to survive past the age of 5. An economist can even monetize the social return/benefit of child mortality reduction and of educating a woman all thanks to our brilliant mind.

Our friend at Economind made a very interesting point and I'll add his whole quote. "Economics is indeed everywhere. A failure to recognize this is a failure to see solution to many problems. Gender empowerment is in every bit and piece economics as it is about gender equality. On top of what you just said, allowing women in labour force will also raise tax revenue and increase marginal productivity of capital, meaning capital investment will yield more return due to larger base of labour force. This boosts economic growth significantly."

Now you understand the massive scope of econ. Well, similar to M&M chocolate candy which comes with many colors, economists can be separated into many kinds as well such as trade economist, financial economist, health economist, agricultural economist, other development economist and so forth. The point is when it comes to allocating scarce resource to its most efficient use, superman has nothing on economists and they are just one call away to save the day. (Congrats to you if you get the Charlie Puth’s reference. Give yourself some kind of reward because you have a good taste, my friends.)

Find our friend Economind athttps://www.facebook.com/economind/?fref=ts

Brands and The Economics of Information

We would like to touch on a subject that is ubiquitous to everyone - brand - which comes to my mind today when we talked about which cinema we should go to watch Finding Dory from my favorite animation studio: Pixar. Some of my favorite Pixar films are “Up, Toy Story 3, Wall-E, Ratatouille and many more. Enough of my praise for Pixar and I will focus instead on coffee, since it’s something that many people know and relish.

The common misconception for many people is that they consider “brand” as something that is of high value and high value and it is a label on a product. While it’s true to a certain extent, it doesn’t completely cover what brand really is. When you think that your co-worker is very genuine and helpful, that’s a brand you attach to your co-worker. Perhaps you think that your co-worker is a hypocrite and manipulative, that’s also brand with which you associate your co-worker. You see, brand goes beyond the label on the product. Brand can extend toward a person, service, a religion and a country. Brand is more than the label per se. Brand basically is the “perception” or “image” you have representing a certain product/service and everything. Even my country Cambodia is putting a lot effort in “rebranding” our country’s image.

Source: https://d.ibtimes.co.uk/en/full/1455968/finding-dory-movie.jpg?w=400 http://funnyand.com/wp-content/uploads/2014/12/Starbucks-Coffee.jpg

There is a reason why a market researcher asks a respondent to tell the researcher the words that come to the mind of the respondent immediately after hearing the name of a product. It goes something like this “What three words come to your mind when you think of Starbucks?” Take 30 seconds to answer this very question yourself. Well, some internet users would comment “Overpriced, Overrated, Overhyped”. Some might say “Quality, Hip/Cool, Cozy/Relax”.

But what brand has anything to do with economics? Well, as I told you in the previous post, you can feel the force of economics almost everywhere you go. Brand has many things to do with the economics of information. Let’s say you drive to a faraway place and you are in need of some caffeine and your favorite drink is hot latte. You have two choices: you can buy your latte at a local coffee shop or at your well-known Starbucks. More often than not, you would get your latte at Starbucks. But why is that? It doesn’t necessarily mean that Starbucks latte is always highly superior to the local shop’s, but you know what to expect of Starbucks latte and service. The local shop’s coffee might be a lot better than the population cafe chain like Starbucks, but we do not have the luxury of having this piece of information. Brand can exerts confidence and quality to the mind of a consumer. This is why a company can spend considerable amount of money on marketing campaign to convince consumers that their products are different than the competitors’ in terms of quality, experience, satisfaction and so on. By planting a particular brand image and perception inside the mind of the consumers, the company of such branded product can design a monopoly (a monopoly is a market situation where there is a single producer of a product and the producer can set a price- price setter) for its own niche market and set the price accordingly.

Normally, a branded product costs more than a generic product. But is it worth it to pay extra for a branded product? Well, if you ask me, I would give a classic reply “it depends”. (Economind, great mind thinks alike) Different people have different perception on a branded product. If you think highly of Starbucks and you derive high utility from consuming Starbucks and you consider the benefits are higher than the cost of Starbuck’s latte, you should go for it. If you are a person who rate Starbucks very low and your utility derived from drinking either Starbucks’ or the local coffee shop’s is the same, then perhaps you would go for the local coffee shop.

Now you know the framework for analysis inside the mind of economists. Just in case you are curious which cinema we are going to watch Dory, it’s Legend. Why? Because our utility derived from either Legend or Major isn't very different and we also gather enough information to make this decision.

Why can't a country print more money to be rich (Part 2): Worst Hyperinflation in History

We touched on the basic economic principle, that is, excessive money printing leads to dramatic rise in price level - inflation. Don’t get me wrong here. Inflation may also be caused by other factors, but we will only stick to money printing as one of the sole factors.  In addition to inflation, the idea of printing more money to be rich is a complete fallacy. We also envisioned a country with extreme money printing and what easy money can do on the price of our beloved sedan Mercedes, clothes, phones, food and other available goods on the market that you can name it. The envisioning is not real and there are a few times when an economic theory and model sounds perfect on the paper but it just does not work in real life due to unrealistic assumptions and other reasons. So as promised we are back again to find examples in real life whether printing more money does indeed bring turmoil to the economy. Before we get into some of the worst inflation, I have to make it clear that the economic notion of money growth and inflation is so complex that economists exchange argument back and forth and I am nowhere near the economists’ status. With that being said, it is possible to learn it the intuitive way by studying previous hyperinflations in the past.

Probably the most well-known hyperinflation in history, at least to me, Weimar Germany’s hyperinflation was a disaster to the economy pioneered by wild money printing. You must have heard of World War I and it is  one of the deadliest war of the modern era due to the modernization of weapon and the massive scale of the war. It is dubbed by historians “The War to End all Wars”, but this world war was followed by another world war began in 1941. Following the end of WWI, Germany was obliged to pay war reparation to other countries. Weimar Germany’s government resorted to money printing to exchange with foreign currency and as a result Germany’s Papiermark’s value fell significantly. A down-to-earth economic concept can be used to explain the devaluation of Papiermark. According to the Working Paper of Steve Hanke and Nicholas Krus, the daily inflation rate was approximately 21% and it took only 3 days and 17 hours for price to double. To put this data into context, price of goods on the market must be changed every hour or even every 10 or 15 minute. The German Mark depreciated to a point when people would use the notes for toilet paper, since it was cheaper to directly use the notes than to purchase the toilet paper.

German’s hyperinflation might be the most well-known but it didn’t earn the title of the worst hyperinflation in history. One of the worst hyperinflation in recent memory was Zimbabwe in 2008 when the inflation rate was 79.6 billion percent following the infamous land reform designed by non other than the chief architect President Robert Mugabe. The land redistribution from the rich white farmers to the local people, many economists believe, led to a dramatic fall in agricultural and manufactured outputs due to the lack of experience and training.  I remember quite vividly when my Corporate Finance Professor showed the class the trillion dollar Zimbabwe dollar note. There were so many zeros that I lost count. Price of goods doubled every 24 hours which must be a headache for those who hold the money. Moneyholders would buy needed items immediately in lunchtime before the price doubled during dinner. So what is the solution to combat this hyperinflation? Well, Zimbabwe ditched their “beloved” Zimbabwe Dollar for other foreign currency such as the US Dollar to restore people's confidence.

The title of the worst hyperinflation in history goes to Hungary after the WWII. Hungary was obliged to pay war reparation to the Soviet Union. At its peak, the monthly inflation rate in Hungary was 13.6 quadrillion percent which means price doubled every 15 hours.  

Central Limit Theorem: The Cristiano Ronaldo of Statistics

I believe whenever you watch a cooking contest, say U.S. Master Chef, you’ll see that Chef Gordon Ramsay, who is one of the three judges on the show, would taste the dish prepared by the contestants normally with only one small spoon. Then he will give his take on the dish whether he thinks the food is good or the food is trash. Chef Ramsay will never make a secret of his disdain for certain food because he will tell you in your face that your food sucks if he thinks it is. Have you ever wondered how he can be sure that he exactly knows how the whole dish taste like with just one single spoon? Well, the answer is simply most of the time one single spoon of the dish can tell you everything that you need to know about the whole dish. In the world of statistics, one spoon of the dish is a representative sample of the whole dish. The whole dish would be referred to as the population. You see, Chef Ramsay does not need to finish the whole dish to know whether the dish is delicious or not. Sure, if he wants to be extremely accurate, he can taste the whole dish, but his opinion on the dish would not be different from the taste of a single spoon. You may wonder “how does food taste test by Chef Ramsay have anything to do with statistics?” Well, it is a great and simple analogy with inferential statistics and especially today’s concept of Central Limit Theorem.

What fascinates me is that we can make a strong statement and inference about the whole population with just a small sample drawn from the population that we attempt to study. Such inference can be done thanks to an elegant concept called Central Limit Theorem (CLT). Economist Charles Wheelan called it the LeBron James of statistics. My inspiration for writing this article is because of Charles as well. For those who does not follow basketball but follow football, the CLT is like the Cristiano Ronaldo of statistics - powerful and elegant.

Before we unravel the gist of the Central Limited Theorem, probably it’s better to start with a simple example inspired by Charles. Let say that the famous school of engineering has a field trip to the beach. The engineering students were randomly assigned to 20 buses and the trip took 5 hours. After 5 hours, 19 buses arrived at the destination except for 1 bus that went missing. You and the rescuers searched the forest and found a bus with several foreign young people who don’t speak your language. Statistics to the rescue!!! You found that the average math score of these people are 65 (assume that everyone is carrying a math report card or you ask everyone to solve a difficult integral question. I know I know, it’s ridiculous but that’s for simplicity). You, as the smartest statistician of the rescuers, sighed and you told everyone that this is not the bus of engineering students. There is no way in hell engineering students who learn all of those complex derivatives and integral would score that low on math (on average). Later, with latest Google Translate technology, we learn that this is the bus of students who major in Khimal (a make-up language and you’ll find no result from Google). This shows why their average math score is not so high because they specialize in language not complex calculation. 

Well guys, that’s it. That’s the Ronaldo of Statistics. That’s Central Limit Theorem. Simply, CLT states that the sample drawn from the population will represent similar characteristics to the population as a whole. A bus of engineering student will be similar to the whole engineering student. A spoon of the dish is very similar to the whole dish. However, each sample drawn from the population will slightly differ from one another but there is a very low probability or low likelihood (unlikelihood???) that the sample is extremely different from the population. It’s just like the average math score of engineering students on each of the 20 buses will slightly differ from the true average math score, but the probability that engineering students on one of the bus have an average math score totally different from the true average math score of all engineering students is very, very low. Yes, there may be some engineering students who would score 65 on math, but it’s highly unlikely that most of the engineering students on the bus that we found would also score 65, as we know that engineering students are very competent in math or they wouldn’t be admitted to engineering school in the first place. Therefore, we can reject that the student bus with an average math score of 65 is not the engineering student group.

Yes, we made it. This is the intuition behind Central Limit Theorem and what’s left is just some calculation and formula related with sample mean and sample standard deviation and the normal distribution, but we won’t touch for today. I think the intuition will help you understand those formula very easily. I hope we can go over the formula in the next post. Until then, please appreciate the beauty of the Ronaldo of Statistics.

               

Hypothesis Testing and Type I and Type II Error: The Murder Trial

Source: http://i.stack.imgur.com/FPCq0.jpg

It has been a while since I last posted an article on this blog. Let's take a break from Economics and take a look at the beauty of Statistics. To be honest, I found Statistics to be very boring during my undergrad. That said, now I'm very intrigued of the power of Statistics. Statistics is more than just about calculating the tedious probability. I now find that probability is a useful foundation in Statistics, but there is more to explore in Statistics. To claim that Statistics is all about probability is like to claim that Economics is all about demand and supply. Anyway, let's get to our topic for today. In Statistics you may have heard about hypothesis testing and the Type 1 and Type 2 error. My Statistics Professor explained this concept in a simple way by using a murder trial as an analogy. In this article, I hope you will have tons of fun learning the concept of hypothesis testing, Type 1 and Type 2 Error. I will keep our discussion simple without getting into any mathematical formula. I hope I can further discuss a real statistics example in the next article.

Hypothesis Testing

Okay, let’s say there is a homicide case in our community and the police arrest a man called Suspect A. We, as a young economist, was hired for no reason to find out whether Suspect A is a murderer. Probably it is because economists love to come up with a statement and love to test whether the statement is correct or false. Therefore, we need to gather evidence and evaluate whether there is sufficient evidence to prove that Suspect A is guilty as charge. This process of evaluating a hypothesized statement based on the evidence is called Hypothesis Testing in Statistics.  

First, we should begin by stating our null hypothesis. A null hypothesis is usually (but not always) the hypothesis which one wants to reject or nullify. In the legal system, generally a person is innocent until proven guilty. Thus, in our murder case, our null hypothesis is that the suspect is innocent. In other words, the suspect did not commit the murder. On the other hand, the alternative hypothesis is the opposite of our null hypothesis and we are trying to find evidence to prove that the alternate hypothesis is correct and reject the null hypothesis. Simply put, the alternative hypothesis in our case is that the suspect killed his wife, which means the man is guilty. Here is the summary so far:

Null Hypothesis: H0: Suspect A is innocent

Alternative Hypothesis: Ha: Suspect A is guilty

Type I and Type II Error

In evaluating the validity and accuracy of our hypothesis, we may unintentionally make two types of mistakes or errors. First, based on our evidence, we may come to a conclusion that the suspect is guilty and sentence an “innocent” person to jail. For this decision, we make a serious mistake and send the poor man to jail for the crime that he did not commit. This is called “Type I Error” in Statistics. In a technical explanation, Type I Error (denoted by alpha) is the probability of rejecting a true hypothesis.

Another mistake that we may make in this murder case trial is that we may not find enough evidence to prove that he is a murderer and acquit (free) the man who in fact is the murder. In this situation, we set free a guilty person. This is known as “Type II Error”. In a formal way, Type II Error is the probability of accepting a false hypothesis.

In summary,

Ruling	In Reality
	The man is innocent	The man is guilty
Sentence the man to jail	Type I Error	Correct Decision
Set the man free	Correct Decision	Type II Error

In general,

Decision	In Reality
	Null hypothesis is true	Null hypothesis is false
Reject null hypothesis	Type I Error	Correct Decision
Accept null hypothesis	Correct Decision	Type II Error

In both of these circumstances, sending an innocent man to prison and setting free a guilty man are both wrong decisions that we want to avoid. I also sum up what we have discussed so far into a simple table. The ideal scenario is to minimize the two types of error. However, we will later learn that Type I and Type II Error are inversely correlated. Hope you are hooked. Ok this is it for today. I hope you now have some intuitive understanding of hypothesis testing, Type I and Type II Error. Next time, I will try to go a bit deeper into the formula to conduct hypothesis testing.